More and more low-latency services are emerging over the Internet and IP (Internet Protocol) networks in general. Examples are interactive video applications, augmented reality, online gaining, future tactile interact applications using haptic or haptic-visual feedback and control, etc. These require data packets to be delivered within a specific time interval (i.e. before a specific deadline), lest they suffer (severe) quality of service degradation. Required maximum latencies reported in the literature range from 150 ms for audio, 50 ms for online gaming, and below 25 ms or even as low as 5 ms or lower for tactile applications.
Current IP networking uses a mechanism of classification, queueing, and scheduling which does not explicitly handle timing (latency) constraints, but at most operates at “best effort with some priorities”. Queueing delays in network elements are variable, and packet marking/drop probabilities depend on queue lengths, which can easily cause a time-critical packet to be dropped while there are less time-critical packets queued for further processing. The dropped packets either need to be retransmitted by the source (adding extra delay) or are simply lost in the communication. End-to-end (multi-hop) latencies can easily vary over tens to even hundreds of milliseconds.
Known approaches use relative priorities, but these are limited and require inefficient computation, or waste resources.
United States Patent Application US20140185628, titled “Deadline aware queue management”, discusses packet delivery deadlines, and describes traffic characteristics comprising deadline state information. The method uses (one or more) traffic characteristics to determine a priority of the packet, and selects a queue based on this priority. There are three queues corresponding to three priority classes: behind-schedule, on-schedule, and ahead-of-schedule. The classification is done by comparing the packet's deadline state information with an expected time to destination for the packet's destination.
However, the method can be ineffective, and generally wastes resources, introduces overhead and is inefficient.